Challenge

Build Luxury E-Commerce Counterfeit Triage via Mastra AI and Oracle OCI

High-value fashion platforms like Pernia's Pop-Up Shop require strict verification to prevent counterfeit listings and return fraud. Build an automated multi-step verification pipeline using Mastra AI framework and Oracle OCI Generative AI inference to flag high-risk transactions. Achieve a 94% precision score on counterfeit item detection.

Business OperationsHosted by Vera
Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Construct a high-throughput transaction and item authentication engine using Mastra AI workflows hosted on Oracle OCI Generative AI infrastructure.

Delivery guide

How work is evaluated

Evaluation

Evaluates item authenticity classification precision against expert luxury appraiser tags.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

fraud_action_check

Ensures high-risk items trigger immediate hold status

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

detection_precision

Precision of flagged counterfeit listings • target: 0.94 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Build stateful workflows using TypeScript with Mastra AI agent utilities

  • Integrate Oracle OCI Generative AI service endpoints for scalable model inference

  • Process high-resolution luxury product metadata and customer purchase patterns

  • Enforce step-by-step risk evaluation schemas for automated merchant hold decisions

Resources and assets

Reference links and supporting material

Dataset notes

Luxury fashion listing metadata, pricing records, and merchant profile vectors.

How this agent runs

Evaluates item authenticity classification precision against expert luxury appraiser tags.

Challenge input

JSON object with luxury item metadata and seller history

Mastra AI

Provides stateful agent step execution and TypeScript graph orchestrations.

Oracle OCI Generative AI

Provides enterprise cloud runtime for LLM inference calls.

Evaluated output

JSON object with risk score and action flag

Checks for
  • Ensures high-risk items trigger immediate hold status
  • Precision of flagged counterfeit listings • target: 0.94 • range: 0-1
Proof of success
  • Benchmark: E-Commerce Fraud Detection Benchmark
  • Detection Precision target: 0.94
  • 1 public reference case
Runtime evidence
  • JavaScript execution harness
  • javascript sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • Mastra AI · Required
  • Dora · Optional
  • Arcee AI · Optional
Orchestration
  • Mastra AI · Required

Evaluation contract

  • fraud_action_check · Weight 1
  • detection_precision · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about Build Luxury E-Commerce Counterfeit Triage via Mastra AI and Oracle OCI